Abstract
The article presents results of a study on search behavior in an interactive query expansion environment. In controlled experiments, users’ search behavior in retrieval system versions with varying levels of query expansion support is compared. On the one hand, the analysis of query logfiles reveals that interactive expansion term suggestions encourage users to utilize a wider variety of term tactics for reformulating their queries than users of a baseline group who are not offered any query expansion support. On the other hand, the experimental results indicate that the interactive expansion functionalities foster the application of facet expansion tactics in favor of the replacement tactic which prevails in system versions that do not offer interactive query expansion support. In summary, the study gives evidence that the implementation of interactive expansion term suggestions adds both to the complexity of the users’ queries and to the variety of their query vocabulary.







Similar content being viewed by others
Notes
The DAFFODIL project is continued and reimplemented in the context of the ezDL project (Easy Access to Digital Libraries, http://ezdl.de/).
As of March 2011, approximately 80% of the documents are in German.
As of March 2011, nearly 40% of the documents in the live implementation of the German Education Index include an abstract and the proportion has continually increased in recent years (see http://www.dipf.de/de/bildungsinformation/pdf/diagramme-zur-fis-bildung-literaturdatenbank/view).
The original prototype was in German.
For a comprehensive description of how the decision regarding which ontological relations to use for identifying expansion terms for the automatic and interactive modes was made, see Carstens [6].
In the example query in Fig. 2, the expansion is partly obsolete because the automatic expansion with Sprachförderungsprogramm (“language support program”) will not deliver any additional documents as compared to the query for Sprachförderung (“language support”).
KMK is the abbreviation for Kultusministerkonferenz: The Standing Conference of the Ministers of Education and Cultural Affairs of the Länder in the Federal Republic of Germany (abbreviation: Standing Conference).
PISA is the abbreviation for Programme for International Student Assessment.
In case a parser mistake occurred more than once in a subject’s search session, this search session was excluded from the analyses to guarantee comparability. The majority of such mistakes was attributable to the fact that the query parser could not interpret queries with leading spaces. In case a parser mistake occurred exactly once, this was not expected to have an impact on the comparability of the search sessions.
The automatic expansion of queries described in Sect. 3.1 is not taken into account in the analyses as the study primarily investigates whether the interactive expansion support has an impact on the users’ query (re-)formulation behavior.
This study does not measure retrieval effectiveness but instead focuses on users’ reformulation behavior. For an analysis of the users’ search effectiveness in the three system versions, e.g. in terms of recall and precision, please refer to Carstens [6].
Project website: http://www.foermig.uni-hamburg.de/web/de/all/org/index.html.
Note that facets may nonetheless have been added to the queries more frequently. However, they are only represented in the graphs in Table 5 if the terms were semantically related to the original query.
References
Bates MJ (1979) Information search tactics. J Am Soc Inf Sci 30(4):205–214
Bates MJ (1990) Where should the person stop and the information search interface start? Inf Process Manag 26(5):575–591
Belkin NJ (1993) Interaction with texts: information retrieval as information seeking behavior. In: Knorz G, Krause J, Womser-Hacker C (eds) Information retrieval ’93: Von der Modellierung zur Anwendung. Universitätsverlag Konstanz, Konstanz, pp 55–66
Buckley C (2004) Why current IR engines fail. In: Proceedings of the 27th annual international ACM SIGIR conference on researchand development in information retrieval (SIGIR 2004). Sheffield, UK, pp 584–585
Carstens C (2009) Integrated ontologies for the semantic web: experiences from modelling a research context ontology. In: Proceedings I-SEMANTICS 2009. Graz, Austria, pp 630–637
Carstens C (2011) Ontology based query expansion—retrieval support for the domain of educational research. Doctoral dissertation. University of Hildesheim, Germany (in press)
Carstens C, Rittberger M, Wissel V (2009) How users search in the German Education Index. Tactics and strategies. In: Proceedings LWA: Lernen – Wissen – Adaption (Workshop Information Retrieval). Darmstadt, Germany, pp 76–83
Carstens C, Rittberger M, Wissel V (2011) Information search behaviour in the German education index. In: Proceedings international conference on digital library management. Kolkata, India, pp 388–398
Dumais ST, Belkin NJ (2005) The TREC interactive tracks: putting the user into search. In: Voorhees EM, Harman DK (eds) TREC. Experiment and evaluation in information retrieval. MIT Press, Cambridge, pp 123–152
Efthimiadis EN (1996) Query expansion. In: Williams ME (ed) Annual review of information systems and technology (31). Information today. Medford, New Jersey, pp 121–187
Fidel R (1985) Moves in online searching. Online Inf Rev 9(1):61–74
Greenberg J (2001a) Automatic query expansion via lexical-semantic relationships. J Am Soc Inf Sci Technol 52(5):402–415
Greenberg J (2001b) Optimal query expansion (QE) processing methods with semantically encoded structured thesauri terminology. J Am Soc Inf Sci Technol 52(6):487–498
Harter SP (1986) Online information retrieval. Concepts, principles and techniques. Academic Press, Orlando
Hersh W, Turpin A, Price S, Chan B, Kramer D, Sacherek L, Olson D (2000) Do batch and user evaluations give the same results? In: Proceedings of the 23rd annual international ACM SIGIR conference on Researchand Development in Information Retrieval (SIGIR 2000). Athens, Greece, pp 17–24
Huang J, Efthimiadis EN (2000) Analyzing and evaluating query reformulation strategies in web search logs. In: Proceedings 18th ACM conference on information and knowledge management (CIKM 2009). Hong Kong, pp 77–86
Ingwersen P (1992) Information retrieval interaction. Taylor Graham, London
Jansen BJ (2000) The methodology of search log analysis. In: Jansen BB, Spink A, Taksa I (eds) Handbook of research on web log analysis. Information science reference, Hershey, pp 100–123
Jansen BJ, Zhang M, Spink A (2007) Patterns and transitions of query reformulation during web searching. International Journal of Web. Inf Syst 3(4):328–340
Järvelin K (2009) Explaining user performance in information retrieval: challenges to IR evaluation. In: Proceedings 2nd international conference on theory of information retrieval. Cambridge, UK, pp 289–296
Kriewel S (2010) Unterstützung beim Finden und Durchführen von Suchstrategien in Digitalen Bibliotheken. Doctoral dissertation. University of Duisburg-Essen, Germany
Kriewel S, Fuhr N (2010) Evaluation of an adaptive search suggestion system. In: Proceedings 32nd European conference on information retrieval research (ECIR 2010), pp 544–555
Kristensen J (1993) Expanding end-users’ query statements for free text searching with a search-aid thesaurus. Inf Process Manag 29(6):733–744
Navigli R, Velardi P (2003) An analysis of ontology-based query expansion strategies. In: Proceedings of the workshop on adaptive text extraction and mining in the 14th European conference on machine learning (ECML 2003), pp 42–49
Rieh SY, Xie H (2006) Analysis of multiple query reformulations on the web: the interactive information retrieval context. Inf Process Manag 42(3):751–768
Ruthven I (2008) Interactive information retrieval. In: Cronin B (ed) Annual review of information science and technology (42). Information today, Medford, New Jersey, pp 43–92
Salton G, McGill M (1983a) Information Retrieval – Grundlegendes für Informationswissenschaftler. McGraw-Hill, New York
Salton G, McGill M (1983b) Introduction to modern information retrieval. McGraw-Hill, New York
Saracevic T (1997) The stratified model of information retrieval interaction: extension and applications. In: Proceedings of the American society for information science, pp 313–327
Smith CL, Kantor PB (2008) User adaptation: good results from poor systems. In: Proceedings of the 31st annual international ACM SIGIR conference on research and development in information retrieval (SIGIR 2008). Singapore, pp 147–154
Song M, Song I-Y, Hu X, Allen RB (2007) Integration of association rules and ontologies for semantic query expansion. Data Knowl Eng 63(1):63–75
Spink A, Wolfram D, Jansen B, Jansen BJ, Saracevic T (2001) Searching the web: the public and their queries. J Am Soc Inf Sci Technol 52(3):226–234
The apache software foundation (2006) Apache lucene—scoring, from http://lucene.apache.org/java/3_1_0/scoring.html. Last access: 23.05.2011
Wildemuth BM, Moore ME (1995) End-user search behaviors and their relationship to search effectiveness. Bull Med Libr Assoc 83(3):294–304
Wilson TD (1999) Models in information behaviour research. J Doc 55(3):249–270
Xie I (2008) Interactive information retrieval in digital environments. IGI Publishing, Hershey
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Carstens, C., Mildner, D. Query Reformulation Behavior in an Interactive Query Expansion Environment. Datenbank Spektrum 11, 161–172 (2011). https://doi.org/10.1007/s13222-011-0069-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13222-011-0069-z